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Analyze US pharmaceutical commercial data to answer complex business questions across brand, sales, marketing, market access, and medical functions. Use SQL and Databricks, with Python where appropriate, to evaluate claims, EMR, prescription, payer, CRM, and digital engagement data. Develop hypotheses, validate findings, and translate results into actionable recommendations for non-technical stakeholders. Prepare Excel and PowerPoint outputs while documenting methodologies, business rules, and analytical results.
๐ง๐ต๐ถ๐ ๐ฟ๐ผ๐น๐ฒ ๐ถ๐ ๐ณ๐ผ๐ฟ ๐ผ๐ป๐ฒ ๐ผ๐ณ ๐๐ต๐ฒ ๐ช๐ฒ๐ฒ๐ธ๐ฑ๐ฎ๐'๐ ๐ฐ๐น๐ถ๐ฒ๐ป๐๐
๐ฆ๐ฎ๐น๐ฎ๐ฟ๐ ๐ฟ๐ฎ๐ป๐ด๐ฒ: ๐ฅ๐ ๐ญ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ - ๐ฅ๐ ๐ฎ๐ฑ๐ฌ๐ฌ๐ฌ๐ฌ๐ฌ (๐ถ๐ฒ ๐๐ก๐ฅ ๐ญ๐ฌ-๐ฎ๐ฑ ๐๐ฃ๐)
Experience: 2+ yrs
Location: Remote (India)
Job Type: Full-time
We are looking for an analytical and commercially minded Commercial Analytics Analyst to support business decision-making for a US oncology pharmaceutical brand. The role involves answering complex, open-ended business questions by analyzing multiple commercial data sources and translating insights into clear, actionable recommendations for non-technical stakeholders.
The ideal candidate will have strong expertise in US pharma commercial data, SQL, Databricks, and business analytics, along with the ability to independently investigate ambiguous questions, apply appropriate business rules, and communicate findings effectively.
RequirementsKey Responsibilities
- Analyze complex and open-ended business questions from commercial stakeholders across Brand, Sales, Marketing, Market Access, and Medical functions.
- Work with diverse US pharma datasets, including claims, EMR/APLD, NRx/TRx, payer, CRM, and digital engagement data.
- Determine the appropriate data source, methodology, and business rules required to answer each analytical question.
- Write, maintain, and optimize SQL queries on Databricks for large-scale datasets.
- Use Python for analytical modelling, automation, and advanced data-processing requirements where appropriate.
- Analyze commercial performance across HCPs, accounts, payers, channels, and other relevant dimensions.
- Work with metrics such as TRx, NRx, market share, line of therapy, and persistency.
- Validate data, investigate inconsistencies, and ensure analytical outputs are accurate and reliable.
- Build upon existing analyses and connect current requests with historical findings to maintain consistency.
- Form hypotheses, test them against available data, iterate on analysis, and independently arrive at meaningful conclusions.
- Translate complex analytical findings into clear, actionable insights for non-technical stakeholders.
- Prepare business-ready outputs and presentations using Excel and PowerPoint.
- Support launch, pre-launch, and post-launch commercial analytics initiatives where required.
- Collaborate with cross-functional stakeholders to understand business context and translate requirements into analytical solutions.
- Maintain clear documentation of analytical approaches, business rules, methodologies, and outputs.
- 2+ years of hands-on experience in US pharmaceutical commercial data analytics.
- Strong experience working with US pharma commercial datasets and business questions.
- Strong proficiency in SQL, with experience working on large datasets and writing queries regularly.
- Hands-on experience with Databricks or a similar data analytics platform.
- Solid understanding of the US pharmaceutical commercial ecosystem, including HCPs, accounts, payers, channels, and commercial metrics.
- Strong understanding of TRx, NRx, market share, line of therapy, and persistency.
- Experience working with claims, EMR/APLD, sales, payer, CRM, and digital engagement data.
- Proven ability to work independently on ambiguous or ad hoc analytical requests.
- Strong analytical thinking with the ability to formulate hypotheses, test assumptions, interpret results, and derive actionable insights.
- Ability to understand data-source limitations and determine when a particular dataset can or cannot answer a business question.
- Strong communication skills with the ability to present analytical findings to non-technical commercial stakeholders.
- Proficiency in Excel and PowerPoint for business analysis and presentation.
- Experience with Python for modelling or automation is an advantage.
- Oncology experience, particularly launch or pre/post-launch analytics, is highly desirable.
- Experience in digital channel, website engagement, or market access analytics is a plus.
- Exposure to tools such as Javelin, Tableau, Power BI, Alteryx, or KNIME is advantageous.
- Experience working in an ad hoc analytics or embedded commercial analytics model is preferred.
- Ability to join immediately or within 15 days will be preferred.
- Strong attention to detail, ownership, problem-solving ability, and commercial orientation.
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